run_on_own_audiofile.ipynb

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   "source": [
    "import keras\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "import glob\n",
    "\n",
    "from audioset import vggish_embeddings\n",
    "\n",
    "\n",
    "audio_embedder = vggish_embeddings.VGGishEmbedder(None)\n",
    "\n",
    "processed_embedding =  audio_embedder.convert_audio_to_embedding('freinds_laugh.wav')\n",
    "\n",
    "embedding_final = np.expand_dims(processed_embedding, axis=0)\n",
    "\n",
    "model = keras.models.load_model('Models/LSTM_ThreeLayer_100Epochs.h5')\n",
    "\n",
    "prediction = model.predict(embedding_final)\n",
    "\n",
    "prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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